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Record W2588858679 · doi:10.3899/jrheum.160546

Methodological Quality of Studies of Endstage Renal Disease in Lupus Nephritis, 1970 to 2015

2017· review· en· W2588858679 on OpenAlexvenueaboutno aff
Maria G. Tektonidou, Michael M. Ward

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsMedicineObservational studyBlindingLupus nephritisIntensive care medicineClinical trialDiseaseSystemic lupus erythematosusInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine trends in methodological quality of studies of endstage renal disease risk in lupus nephritis, 1970-2015. METHODS: We assessed quality using the Newcastle-Ottawa scale for observational studies, and the Cochrane Collaboration's risk-of-bias tool for trials. RESULTS: In observational studies, description of enrollment criteria was high but decreased over time. Adequacy of followup was low but improved. Inception cohorts and community-based studies were uncommon. Trials had low risk of bias in blinding and selective outcome reporting but most had unclear risks in sequence generation and allocation concealment. CONCLUSION: Methodological quality was mixed, with limited improvement over time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.158
metaresearch head score (Gemma)0.388
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.842
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1580.388
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.013
Bibliometrics0.0140.012
Science and technology studies0.0010.002
Scholarly communication0.0060.003
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.508
GPT teacher head0.556
Teacher spread0.048 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designSystematic review
DomainMethods
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes2
Has abstractyes

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